columns
The view columns contains information about all
table columns (or view columns) in the database. System columns
(oid, etc.) are not included. Only those columns are
shown that the current user has access to (by way of being the
owner or having some privilege).
Table 37.14. columns Columns
| Name | Data Type | Description |
|---|---|---|
table_catalog | sql_identifier | Name of the database containing the table (always the current database) |
table_schema | sql_identifier | Name of the schema containing the table |
table_name | sql_identifier | Name of the table |
column_name | sql_identifier | Name of the column |
ordinal_position | cardinal_number | Ordinal position of the column within the table (count starts at 1) |
column_default | character_data | Default expression of the column |
is_nullable | yes_or_no |
YES if the column is possibly nullable,
NO if it is known not nullable. A not-null
constraint is one way a column can be known not nullable, but
there can be others.
|
data_type | character_data |
Data type of the column, if it is a built-in type, or
ARRAY if it is some array (in that case, see
the view element_types), else
USER-DEFINED (in that case, the type is
identified in udt_name and associated
columns). If the column is based on a domain, this column
refers to the type underlying the domain (and the domain is
identified in domain_name and associated
columns).
|
character_maximum_length | cardinal_number |
If data_type identifies a character or bit
string type, the declared maximum length; null for all other
data types or if no maximum length was declared.
|
character_octet_length | cardinal_number |
If data_type identifies a character type,
the maximum possible length in octets (bytes) of a datum; null
for all other data types. The maximum octet length depends on
the declared character maximum length (see above) and the
server encoding.
|
numeric_precision | cardinal_number |
If data_type identifies a numeric type, this
column contains the (declared or implicit) precision of the
type for this column. The precision indicates the number of
significant digits. It can be expressed in decimal (base 10)
or binary (base 2) terms, as specified in the column
numeric_precision_radix. For all other data
types, this column is null.
|
numeric_precision_radix | cardinal_number |
If data_type identifies a numeric type, this
column indicates in which base the values in the columns
numeric_precision and
numeric_scale are expressed. The value is
either 2 or 10. For all other data types, this column is null.
|
numeric_scale | cardinal_number |
If data_type identifies an exact numeric
type, this column contains the (declared or implicit) scale of
the type for this column. The scale indicates the number of
significant digits to the right of the decimal point. It can
be expressed in decimal (base 10) or binary (base 2) terms, as
specified in the column
numeric_precision_radix. For all other data
types, this column is null.
|
datetime_precision | cardinal_number |
If data_type identifies a date, time,
timestamp, or interval type, this column contains the (declared
or implicit) fractional seconds precision of the type for this
column, that is, the number of decimal digits maintained
following the decimal point in the seconds value. For all
other data types, this column is null.
|
interval_type | character_data |
If data_type identifies an interval type,
this column contains the specification which fields the
intervals include for this column, e.g., YEAR TO
MONTH, DAY TO SECOND, etc. If no
field restrictions were specified (that is, the interval
accepts all fields), and for all other data types, this field
is null.
|
interval_precision | cardinal_number |
Applies to a feature not available
in PostgreSQL
(see datetime_precision for the fractional
seconds precision of interval type columns)
|
character_set_catalog | sql_identifier | Applies to a feature not available in PostgreSQL |
character_set_schema | sql_identifier | Applies to a feature not available in PostgreSQL |
character_set_name | sql_identifier | Applies to a feature not available in PostgreSQL |
collation_catalog | sql_identifier | Name of the database containing the collation of the column (always the current database), null if default or the data type of the column is not collatable |
collation_schema | sql_identifier | Name of the schema containing the collation of the column, null if default or the data type of the column is not collatable |
collation_name | sql_identifier | Name of the collation of the column, null if default or the data type of the column is not collatable |
domain_catalog | sql_identifier | If the column has a domain type, the name of the database that the domain is defined in (always the current database), else null. |
domain_schema | sql_identifier | If the column has a domain type, the name of the schema that the domain is defined in, else null. |
domain_name | sql_identifier | If the column has a domain type, the name of the domain, else null. |
udt_catalog | sql_identifier | Name of the database that the column data type (the underlying type of the domain, if applicable) is defined in (always the current database) |
udt_schema | sql_identifier | Name of the schema that the column data type (the underlying type of the domain, if applicable) is defined in |
udt_name | sql_identifier | Name of the column data type (the underlying type of the domain, if applicable) |
scope_catalog | sql_identifier | Applies to a feature not available in PostgreSQL |
scope_schema | sql_identifier | Applies to a feature not available in PostgreSQL |
scope_name | sql_identifier | Applies to a feature not available in PostgreSQL |
maximum_cardinality | cardinal_number | Always null, because arrays always have unlimited maximum cardinality in PostgreSQL |
dtd_identifier | sql_identifier | An identifier of the data type descriptor of the column, unique among the data type descriptors pertaining to the table. This is mainly useful for joining with other instances of such identifiers. (The specific format of the identifier is not defined and not guaranteed to remain the same in future versions.) |
is_self_referencing | yes_or_no | Applies to a feature not available in PostgreSQL |
is_identity | yes_or_no |
If the column is an identity column, then YES,
else NO.
|
identity_generation | character_data |
If the column is an identity column, then ALWAYS
or BY DEFAULT, reflecting the definition of the
column.
|
identity_start | character_data | If the column is an identity column, then the start value of the internal sequence, else null. |
identity_increment | character_data | If the column is an identity column, then the increment of the internal sequence, else null. |
identity_maximum | character_data | If the column is an identity column, then the maximum value of the internal sequence, else null. |
identity_minimum | character_data | If the column is an identity column, then the minimum value of the internal sequence, else null. |
identity_cycle | yes_or_no |
If the column is an identity column, then YES if the
internal sequence cycles or NO if it does not;
otherwise null.
|
is_generated | character_data | Applies to a feature not available in PostgreSQL |
generation_expression | character_data | Applies to a feature not available in PostgreSQL |
is_updatable | yes_or_no |
YES if the column is updatable,
NO if not (Columns in base tables are always
updatable, columns in views not necessarily)
|
Since data types can be defined in a variety of ways in SQL, and
PostgreSQL contains additional ways to
define data types, their representation in the information schema
can be somewhat difficult. The column data_type
is supposed to identify the underlying built-in type of the column.
In PostgreSQL, this means that the type
is defined in the system catalog schema
pg_catalog. This column might be useful if the
application can handle the well-known built-in types specially (for
example, format the numeric types differently or use the data in
the precision columns). The columns udt_name,
udt_schema, and udt_catalog
always identify the underlying data type of the column, even if the
column is based on a domain. (Since
PostgreSQL treats built-in types like
user-defined types, built-in types appear here as well. This is an
extension of the SQL standard.) These columns should be used if an
application wants to process data differently according to the
type, because in that case it wouldn't matter if the column is
really based on a domain. If the column is based on a domain, the
identity of the domain is stored in the columns
domain_name, domain_schema,
and domain_catalog. If you want to pair up
columns with their associated data types and treat domains as
separate types, you could write coalesce(domain_name,
udt_name), etc.